Search Results for author:
Found 15 papers, 7 papers with code
Self-supervised Learning of Neural Implicit Feature Fields for Camera Pose Refinement
We learn the underlying geometry of the scene with an implicit field through volumetric rendering and design our feature field to leverage intermediate geometric information encoded in the implicit field.
4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements
This work presents 4DHumanOutfit, a new dataset of densely sampled spatio-temporal 4D human motion data of different actors, outfits and motions.
SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization
Inspired by properties of semantic segmentation, in this paper we investigate how to leverage robust image segmentation in the context of privacy-preserving visual localization.
Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark
In order to investigate the consequences for visual localization, this paper focuses on understanding the role of image retrieval for multiple visual localization paradigms.
On the Limits of Pseudo Ground Truth in Visual Camera Re-localisation
This begs the question whether the choice of the reference algorithm favours a certain family of re-localisation methods.
Large-scale Localization Datasets in Crowded Indoor Spaces
In this paper, we introduce 5 new indoor datasets for visual localization in challenging real-world environments.
Robust Automatic Monocular Vehicle Speed Estimation for Traffic Surveillance
Experimental results conducted on three diverse benchmarks demonstrate excellent speed estimation accuracy that could enable the wide use of CCTV cameras for traffic analysis, even in challenging conditions where state-of-the-art methods completely fail.
Benchmarking Image Retrieval for Visual Localization
This paper focuses on understanding the role of image retrieval for multiple visual localization tasks.
Robust Image Retrieval-based Visual Localization using Kapture
To demonstrate this, we present a versatile pipeline for visual localization that facilitates the use of different local and global features, 3D data (e. g. depth maps), non-vision sensor data (e. g. IMU, GPS, WiFi), and various processing algorithms.
Virtual KITTI 2
This paper introduces an updated version of the well-known Virtual KITTI dataset which consists of 5 sequence clones from the KITTI tracking benchmark.
R2D2: Reliable and Repeatable Detector and Descriptor
We thus propose to jointly learn keypoint detection and description together with a predictor of the local descriptor discriminativeness.
Ranked #2 on
Camera Localization
on Aachen Day-Night benchmark
R2D2: Repeatable and Reliable Detector and Descriptor
In this work, we argue that salient regions are not necessarily discriminative, and therefore can harm the performance of the description.
From handcrafted to deep local features
This paper presents an overview of the evolution of local features from handcrafted to deep-learning-based methods, followed by a discussion of several benchmarks and papers evaluating such local features.
Analyzing Computer Vision Data - The Good, the Bad and the Ugly
However, major questions concerning quality and usefulness of test data for CV evaluation are still unanswered.
CV-HAZOP: Introducing Test Data Validation for Computer Vision
This checklist can be used to evaluate existing test datasets by quantifying the amount of covered hazards.
